非凸控制约束下多智能体系统一致性和包含分析:终端迭代学习策略  

Multi-agent systems consensus and containment analysis undernonconvex control constraints: a terminal iterative learningstrategy

作　　者：罗子健 熊文军 曹进德 Zijian LUO;Wenjun XIONG;Jinde CAO(Faculty of Science,Civil Aviation Flight University of China,Chengdu 641419,China;School of Automation Engineering,University of Electronic Science and Technology of China,Chengdu 611731,China;School of Mathematics,Southeast University,Nanjing 211189,China)

机构地区：[1]中国民用航空飞行学院理学院,成都641419 [2]电子科技大学自动化工程学院,成都611731 [3]东南大学数学学院,南京211189

出　　处：《中国科学:信息科学》2025年第1期140-155,共16页Scientia Sinica(Informationis)

基　　金：国家重点研发计划(批准号:2020YFA0714300);国家自然科学基金(批准号:62373308);中央引导地方科技发展资金(批准号:2023ZYD0009)资助项目。

摘　　要：本文通过设计非凸控制约束条件下的迭代学习控制策略,解决多智能体系统的一致性和包含控制问题.此类问题的难点在于缺乏一种有效工具来处理分布式控制中的非凸约束.为此,本文综合非凸约束算子方法提出了一类新颖的迭代学习策略,并将其用于非凸约束下的多智能体一致性分析中.进一步,通过设计非凸约束下的终端迭代学习策略,探讨了相关的包含控制问题,即使各节点在终端时刻的状态收敛到领导者状态生成的凸包内.本文在迭代学习的框架下,结合压缩映射和Lyapunov稳定性理论,分别给出了非凸约束下实现一致性或包含的充分性条件.最后,通过两个数值模拟来说明本文理论结果的有效性.This paper aims to address the consensus and containment control problems of multi-agent systems by designing iterative learning controllers in the presence of nonconvex constraints.A difficulty in solving such problems is the lack of an efficient tool for dealing with the nonconvex constraints in distributed control.To tackle the issue,this paper proposes a novel class of iterative learning strategies in line with the nonconvex constraint operator approach.Then,we apply them in consensus analysis of multi-agent systems under the constraints.Furthermore,the containment control problem of multi-agent systems is investigated by designing terminal iterative learning strategies in the presence of nonconvex constraints where the coordination objective is to make the states of agents at the terminal time converge into the convex hull generated by those of the leaders.Under the framework of iterative learning control,combined with the contractive mapping technique and Lyapunov stability theory,some sufficient conditions are established for consensus and containment problems with terminal iterative learning strategies under nonconvex constraints.Finally,two numerical simulations are presented for illustration.

关 键 词：非凸约束 终端迭代学习 一致性 包含控制 收敛性分析 

分 类 号：TP13[自动化与计算机技术—控制理论与控制工程]